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# Names
dict_name = dict(zip(["A", "B", "C", "D", "E", "F"], 
                     ["Lemon Cake", "Sandwich", "Chocolate Cake", "Croissant", "Chocolate Eclair", "Panini"]))

# Solve Model
model.solve()
for v in model.variables():
    print(dict_name[v.name], "=", int(v.varValue))
print("Profit reached: {:,} euros".format(sum(var_dict[i].varValue * profit[i] for i in items)))

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# Define Objective Function
model += lpSum([profit[i] * var_dict[i] for i in items])

# 4. Define Constraints 
# Bakers
model += lpSum([var_dict[i]*baker[i] for i in items]) <= 24*60
# Oven
model += lpSum([var_dict[i]*oven[i] for i in items]) <= 48*60
# Assistant
model += lpSum([var_dict[i]*assist[i] for i in items]) <= 4*60

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from ortools.constraint_solver import routing_enums_pb2
from ortools.constraint_solver import pywrapcp
import pandas as pd
import numpy as np

# Import Distance Matrix 
df_distance = pd.read_excel('df_distance_matrix.xlsx', index_col=0)
# Transform to Numpy Array
distance_matrix = df_distance.to_numpy()

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# Calculate Distance between two nodes
def distance_callback(from_index, to_index):
    """Returns the distance between the two nodes."""
    # Convert from routing variable Index to distance matrix NodeIndex.
    from_node = manager.IndexToNode(from_index)
    to_node = manager.IndexToNode(to_index)
    return data['distance_matrix'][from_node][to_node]
    
# Get the order quantity of each node (location)
def demand_callback(from_index):

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# Create the routing index manager.
manager = pywrapcp.RoutingIndexManager(len(data['distance_matrix']),
                                       data['num_vehicles'], data['depot'])

# Create Routing Model
routing = pywrapcp.RoutingModel(manager)

# Create and register a transit callback.
transit_callback_index = routing.RegisterTransitCallback(distance_callback)

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if solution:
    total_distance = 0
    total_load = 0
    for vehicle_id in range(data['num_vehicles']):
        index = routing.Start(vehicle_id)
        plan_output = 'Route for driver {}:\n'.format(vehicle_id)
        route_distance = 0
        route_load = 0
        while not routing.IsEnd(index):
            node_index = manager.IndexToNode(index)

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import pandas as pd
from pulp import *

# Import Nutrition Facts
nutrition = pd.read_excel('Nutrition Facts.xlsx', index_col = 0)
# Import Costs
costs = pd.read_excel('Costs.xlsx')
dict_costs = dict(zip(costs['Ingredients'], costs['Costs']))

# Variables